Sleep quality monitoring in individual sports athletes: parameters and deﬁnitions by systematic review

In the present review, we identify which instruments and parameters are used for sleep quality monitoring in individual sport athletes and which deﬁnitions were used for sleep quality parameters in this literature ﬁeld. Systematic searches for articles reporting the qualitative markers related to sleep in team sport athletes were conducted in PubMed, Scopus and Web of Science online databases. The systematic review followed the Preferred Reporting Items for Systematic Reviews. The initial search returned 3316 articles. After the removal of duplicate articles, eligibility assessment, 75 studies were included in this systematic review. Our main ﬁndings were that the most widely used measurement instruments were Actigraphy (25%), Rating Likert Scales (16%) and Sleep Diary (13%). On sleep quality parameters (Sleep duration = 14%; Wake after sleep onset = 14%; Sleep Quality = 12%; Sleep Effciency = 11% and Sleep Latency = 9%), the main point is that there are different deﬁnitions for the same parameters in many cases reported in the literature. We conclude that the most widely used instruments for monitoring sleep quality were Actigraphy, Likert scales and Sleep diary. Moreover, the deﬁnitions of sleep parameters are inconsistent in the literature, hindering the understanding of the sleep-sport performance relationship.


INTRODUCTION
Good sleep quality is a well-recognized predictor of physical and mental health, wellness and overall vitality 1 ; conversely, a poor sleep quality may lead to accumulation of fatigue, drowsiness and changes in mood 2 . Due to this importance, sleep has been a topic much researched and debated recently in the sporting context 3,4 . In this context, when it comes to establishing goals for athletes' sleep, most recommendations focus on the number of hours spent in bed and on sleep hygiene strategies 2 . Although the number of hours in bed is a good reference to start improving sleep, athletes need to focus on sleep quality as well. Sleep quality refers to how well you sleep 1 . Uninterrupted sleep allows you to achieve the ideal amount of restorative sleep, which is essential for athletes 2,5 . However, the quality of sleep can be more difficult to measure than the amount of sleep 1 , especially in athletes.
Researchers verified the effects of training and competition on the sleep of elite athletes 4 . They found that their sleep quality, measured by sleep efficiency, was lower (3%-4%) the night before the competition compared with previous nights. The literature has shown that the sleep of the athletes was impaired on at least 1 night before an important competition 4,5 . Furthermore, in sports practice differences have been observed in the sleep characteristics between individual and team sport athletes 5,6 . Some of these characteristics are related with the sleep quality of the athletes 5 . For example, individual sport athletes had poorer sleep efficiency than team sports athletes 6 . In individual sports, the results of athletes are entirely their own. However, they do not have teammates to rely on or share the burden of a loss. Thus, pre-competition stress can contribute to reduced sleep and poor sleep quality 2,5 .
The term "sleep quality" has long been poorly defined yet ubiquitously used by researchers, clinicians and patients 7 .
In addition, measuring sleep quality is more difficult than the amount of sleep because sleep quality is a subjective experience 1 .This situation still remains, as reported by a recent systematic review and meta-analysis, which pointed to the best parameters for sleep quality monitoring in team sport athletes 3 . Therefore, the aims of the present study were to identify: 1) which instruments and parameters are used for sleep quality monitoring in individual sport athletes; and 2) which definitions were used for sleep quality parameters in in this literature field.

Procedure
As a review methodology, we adopted the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines 8 . The selection process and data extraction methods were completed by six authors (JGC, HSS, MS, CACF, RG and RRB). The quality appraisal was completed by two authors (JGC and RRB).

Search Strategy
Three electronic databases (PubMed, Scopus and Web of Science) were systematically searched from inception up to March 21st, 2020. The command line ("sleep" OR "sleep quality" OR "sleep quantity" OR "sleep behavior" OR "sleep disturbance" OR "sleep deprivation" OR "circadian rhythm") AND ("individual sport" OR "individual sports" OR "athlete" OR "athletes") was used during the electronic search.

Eligibility criteria and selection process
Three authors (JGC, HdSS and MS) reviewed and identified the titles and abstracts based on the following inclusion criteria: 1. The study was written in English; 2. The study was published as an original research in a peer-reviewed journal as a full text article 3. Data were reported specifically for individual sport athletes; 4. Study performed during the athlete's sporting career; 5. The participants were competitive athletes (defined as Olympic, Paralympic, international, professional, semi-professional, national, regional, youth elite or division I collegiate); 6. Sleep quality parameters were included; 7. The participants had not used chronic medication/ drugs.

Quality Assessment
Two authors (JGC and RRB) evaluated the quality of all studies using evaluation criteria (Table 1) based on a study by Saw et al. 9 and used by Claudino et al. 3 . Scores were allocated based on how well each criterion was met, assuming a maximum possible score of 8 (low risk of bias) if some doubt was found, the third author (JCS) made the decision. Studies with a risk of bias score 4 or less were considered poor and were excluded.

RESULTS
The initial search returned 3316 articles ( Figure 1). After the removal of duplicate articles (n=1568), a total of 1748 studies were retained for full-text screening. Following the eligibility assessment, 1657 studies were excluded, as they did not meet the set inclusion criteria. Thus, 76 studies published between 1997 and 2020 were included for assessing the risk of bias. After that phase, we included 75 studies in this systematic review.

Findings
Initially, to permit an adequate reading flow, the summaries of the 75 studies included in the systematic review are described online supplementary in a table. Twenty-one measurement instruments were used for monitoring sleep quality in individual sport athletes ( Table 3). The following instruments were the most prevalent: Actigraphy (n=36; 25%); Rating Likert Scales (n=23; 16%) and Sleep Diary (n=18; 13%).
The definition and procedures used for the sleep quality parameters are presented in Table 4. Regarding sleep quality parameters (Sleep duration = 14%; Wake after sleep onset = 14%; Sleep Quality = 12%; Sleep Efficiency = 11% and Sleep Latency = 9%), there are different definitions for the same parameters in many cases reported in the studies.

DISCUSSION
Many athletes and coaches know that having a good night's sleep is important. However, despite this, they are constantly having far less than they actually need. Like this, in this study we found which instruments, parameters and their definitions were used for sleep quality monitoring in individual sport athletes. Our main findings were that the measurement instruments most used were actigraphy, scales as Likert rating scales and sleep diary. Additionally, there are different definitions for the same parameters in many cases reported in the literature. The definition of sleep quality appeared in only one study, being determined by measures of sleep efficiency and fragmentation index.
Despite the influence that sleep has on sports performance, the present study is the first to show how the measurement instruments for monitoring the sleep in the individual sports were used. Previous research with team sport athletes 3 reported similar results to those of the present study. In general, the scientific literature suggests the use of sleep diaries, actigraphy, or polysomnography for clinical suspicion of sleep disorders evaluation 16,79,89 . The use of screening questionnaires contributes to identify poor sleep habits and potential sleep disorders 16 . The data obtained from the diaries and questionnaires can be informative for practitioners because the process is simple. The association of the sleep diary with actimetry has been recommended, because it is useful for tracking the sleep-wake pattern and for ensuring adequate time in bed 89,90,91 . This method is more adequate during periods of travel or high-intensity training, when there is high risk for insufficient sleep 90 .
Also, the specificity of training and competition schedules is possibly the most influential factor that leads to inconsistent sleep among individual sports athletes 108 . For this reason, instruments with practical applications are more  initiation, sleep maintenance, sleep quantity, and refreshment upon awakening". Sleep quality refers to subjective perceptions of one's sleep, that should be borne in mind in coaching athletes before, during and after the competitions 16,60,71,106,111 . Like this, we highlight the role of sleep quality in individual sports is still an unexplored field of research. For this reason, understanding the sports requirements is vital for adequate sleep, as well as, for adequate sleep evaluation. Each sport represents a unique variable combination to deal with sleep management. Disturbed sleep patterns and increased incidences of illness have been shown in ultra-endurance athletes 85 and sprint cyclists 86,87 . It has been observed a greater reporting of poor sleep in individual sports compared with team sports 88 . These differences were explained by the lower pressure and anxiety experienced in team sports compared with individual ones due to the performance responsibility, e.g., in team-sports, being divided by the team members 3,92 . Conversely, individual sports athletes could go to bed earlier, wake up earlier, and obtain less sleep than athletes from team sports 6 . This feature may favor a sleep debt condition and then, impairment of aspects related to physical restoration, compromising sports performance.
From a practical point of view, individual and team sports differ in most aspects, but mainly the dimension of the sport's internal logic. Internal logic is defined as a system of specific motor characteristics necessary for the performance of particular sports gestures 80 . In addition, internal logic is associated with aspects of a modality that never changes, such as the existence of interaction with opponents. This means, if there are peculiar aspects of the modalities (individual or team-sports) which require that the players act in a specific way (from the point of view of the realized movement) during their practice. Thus, in team sports, there will usually be interaction with adversary whereas in individual sports, interaction with adversary may or may not exists 3 . In addition, the duration and intensity of the individual or team modalities are also very different. These differences may influence, to a great extent, the type of stress generated, the state of mood and, consequently, the sleep duration or sleep quality in different sports modalities 81,82,83,84 .
Properly addressing the sleep needs of athletes requires understanding the complexity of variables influencing circadian and homeostatic factors and cooperation of a multidisciplinary team of coaches and physicians. Sleep management should include goals to all athletes as well as individualized approaches 16 . In this context, is necessary strategies of education about healthy sleep habits and sleep hygiene 1,16 . Besides, cooperation of coaches and staff to identify athletes at risk and, the identification of outside factors influencing sleep, including stress, injuries and medications are fundamental for sleep monitoring of the athletes 16 .
The results of this review suggest that sleep quality should be studied in individual sport athletes using easy and inexpensive methods, such as questionnaires/diary, actigraphy or Likert rating scales. The current state of development in the area proposes a promising future suitable for monitoring the sleep quality of athletes 16 . Thus, the use of activity monitors (actigraphy), smartphone applications and sleep questionnaires have become a reality in athletes' daily practice 16,89,-109 . In this sense, different instruments and information collected can complement each other and aggregate sleep data makes the assessment of sleep quality more robust and tolerant to noise and lack of data 109 . Our results signaling for the use of actigraphy, rating Likert scales and sleep diary for sleep monitoring. We, therefore, suggest that this holistic approach (individualized) to sleep assessment be used in individual sports. On the other hand, the use of adequate instruments is of no use if the analyzed parameters are not properly defined. In our study, we identified different parameters for assessing sleep quality. In this regard, the National Sleep Foundation (NSF) recommended that the main variables that express sleep quality are latency, a number of an awakenings (>5 minutes), wake after sleep onset (WASO) and sleep efficiency 1 . However, the NSF did not find consensus regarding sleep architecture or nap-related variables as elements of good sleep quality 1 . This fact explains why we found only one study 22 that defined sleep quality. Despite its common usage, the literature highlights which sleep quality is a term without a clear definition 1,7 . However, Kline 110 defines sleep quality "as one's satisfaction with the sleep experience, integrating aspects of sleep about the use of artificial intelligence (AI) to integrate sleep quality in the 24-h monitoring of the athletes 112 . This is because the trend of using 24-hour monitoring (wearable devices or smartphones) and the use of prediction algorithms can contribute to discovering how sleep quality can be improved in athletes. Improving athletes' sleep quality is important because it is vital for levels of mental and physical performance, general well-being and for the recovery process. Sleep-related technologies are useful for monitoring and also for aid intervention 109 .
The main limitation of our study was not to analyze the level of instability (coefficient of variation) of the sleep quality parameters due to the impossibility of grouping given the different definitions for the same parameter. The literature 3 suggests a scale for the CV with CV >30%=large and CV <10%=small 3 . Variables with a large CV are less likely (OR) to detect statistically significant differences during repetitive measurement. In the case of monitoring the quality of sleep, performing this analysis contributes to better reliability of the measures repeated daily or in specific situations (jet lag, training, competition, etc.).
In conclusion, the present study found that the instruments most widely used for monitoring sleep quality were actigraphy, Likert rating scales and questionnaires. Moreover, the definitions of sleep parameters are inconsistent in the literature. This situation does not favour the understanding of the sleep-sport performance relationship. Thus, we suggest creating an international consensus for sleep evaluation in highperformance athletes.

FUNDING SOURCE
This study was supported out on the financial support of the National Council for Scientific and Technological Development (CNPq) by process 432153/2018-7 (MCTIC/ CNPq Nº 28/2018).        n/a

1) Pittsburgh Sleep Quality Index (PSQI) and 1) Epworth Sleepiness Scale (ESS).
The PSQI Score ranges from 0 to 21, and higher scores reflect poorer-quality sleep. On the ESS, athletes must to determine the chance of falling sleep in each of the presented situations, scoring likelihood from 0 (no chance) to 3 (high chance). The ESS Score ranges between normal (from 0 to 6); ESS limit (from 7 to 9); ESS slight (from 10 to14); ESS moderate (from 15 to 20); ESS high (above 20). These ratings were recorded during the preparation period for Paralympic games between 9 am and 11 am. Validity information was provided.   Determine the sleep quality before and during competition and whether sleep on the nights before and during competition was related to overall performance ranking.
n/a 6) Actigraphy (Philips Respironics, Bend, OR, USA), 1) Self-report sleep diaries and 3) A Likert-type scale ranging from 1 (very good) to 5 (very poor) (sleep quality). The sleep diary indicated the participant was lying down attempting to sleep and the activity counts derived from the activity monitor were sufficiently low to indicate that the participant was immobile. Once these conditions were met simultaneously, time was scored as sleep. Measurements: bedtime, get-up, sleep offset time, sleep onset time, sleep latency, time in bed, total sleep time, sleep efficiency, mean activity score.  The effect of a simulated grand tour on sleep, mood and the general well-being of competitive cyclists. 06 8) Actigraphy (Philips Respironics, Bend, OR, USA), 2) Self-report sleep diaries, and 2) Visual analogue scale (VAS; 100mm). This was achieved using the Phillips Respironics' Actiwatch Algorithm where time was scored as wake unless: 1) the sleep diary indicated the participant was lying down attempting to sleep; and 2) the activity counts derived from the activity monitor were sufficiently low to indicate that the participant was immobile. And the VAS were measured via this question of VAS "Please rate how you feel this morning" according to the subscale (e.g. sleep quality) by placing a mark on a standard linear non-numeric bipolar Visual Analogue Scale (VAS) that consisted of a 100mm line with anchors "very poor" and 'very good' at either end. For VAS, no information on validity and reliability (no reference was provided Investigate the habitual sleep/wake behavior of elite athletes, and to compare the differences in sleep between athletes from individual and team sports. n/a 9) Actigraphy (Philips Respironics, Bend, OR, USA), 3) Self-report sleep diaries, and 4) A Likert-type scale ranging from 1 (very good) to 5 (very poor) (sleep quality). This was achieved using the Phillips Respironics' Actiwatch Algorithm where time was scored as wake unless: 1) the sleep diary indicated the participant was lying down attempting to sleep; and 2) the activity counts derived from the activity monitor were sufficiently low to indicate that the participant was immobile. The measurements were: sleep offset time, sleep onset time, sleep latency, sleep efficiency, and mean activity score. For Likert scale, no information on validity and reliability (no reference was provided). Effects of athlete's profile of distinguishing "success" and "failure" of outcomes from a major competition on biomarkers, self-reported mood states and sleep.    . The GT3X data were scored and analyzed using ActiLife 6.9.2. Validity and reliability information were reported. Participants wore the actigraphs on the non-dominant wrists except when swimming or showering. The PDSS is an 8-item self-report questionnaire that Items include "How often do you fall a sleep or feel drowsy in class?" and "Are you usually alert during the day?". Total scores range from 0 to 32, with higher scores indicating greater daytime sleepiness. Information of validity or reliability was reported.
Jiu-jitsu (n=84) Swimming (n=75) Triathlon (n=9) Sailing (n=37) Judo (n=20) Gymnastics (n=11) Taekwondo (n=15) Age: 22 ± 7 y International and National To describe the perceived sleep quality and mood states of elite athletes during a competitive period, and clarify their relationship to athletes' sport performance n/a 11) A Likert-type scale ranging from 1 to 5 (sleep quality).The question on selfreported sleep quality was "How would you evaluate the quality of your sleep in the past few days?" Participants rated their sleep quality on a Likert-type scale as follows: 1 = very bad, 2 = bad, 3 = normal, 4 = good and 5 = excellent. We also recorded participants' age, sport modality (individual or team), and years of practice in their sports.

Crowcroft
Swimming (n=14; 11M, 3F) Age 21 ± 3 y National To report the week-to-week variability, reliability, and signal-to-noise ratio in common athlete-monitoring tools and to assess the diagnostic characteristics of these tools to identify improvements and decrements in performance.  19) Actigraphy (Readiband, Sync software), 8) Sleep diary, 1) Insomnia Severity Index (ISI), 3) Epworth Sleepiness Scale (ESS) and 1) Berlin Questionnaire Activity monitors were worn on the non-dominant wrist throughout the monitoring period, including during training and sparring. An activity monitor and a sleep/training diary was issued to each athlete at 20:00 on the evening of day 1 (night 1) and retrieved on the morning of day 7 (after night -6). Sleep-related measures were derived from each device. These included SD, SL, time of SO, wake after SO, SE and time at wake (WT).Diary. Athletes were provided with a sleep/training diary, which they carried with them throughout the study period. The diary contained questions relating to their sleep, electronic device use, caffeine use, and training effort. The ISI consists of 5 separate questions that ask the participant to self-rate their own experience with insomnia, each with a scale of 0-4. The questions relate to severity, satisfaction, notice ability and worry or distress associated with their insomnia. Scores were aggregated and assessed against a criterion. A score greater than 15 indicates clinical insomnia.
The ESS is a self-reported scale that asks how likely an individual is to doze off or fall asleep in common daytime situations. Scores in excess of 9 indicate excessive daytime sleepiness. Obstructive sleep apnea (OSA) risk was assessed using the Berlin Questionnaire, which assigns risk of OSA based on the presence and frequency of snoring behavior, wake time sleepiness or fatigue, and a history of obesity and/or hypertension. A positive response to 2 or more of these categories indicates risk for OSA. Validity and reliability information were provided.
Cycling (n=10; M) Age: 23 ± 4 y National and Regional The effects of two shortterm arrival strategies for competitions at moderate altitude on endurance performance. Swimming (n=9; 2M, 7F) Age: 12 ± 2 y Regional To analyze the association between HRV and three psychological correlates of performance: mood, self-esteem, and sleep quality, and to analyze the association between these variables and performance. The effect of competition on cognitive control and autonomic nervous system responsiveness in male elite and sub-elite gymnasts, and evaluate whether pain ratings would relate to training loads and cognitive capacity. To characterize a range of psychological responses at select stages of a competitive season in Division I collegiate rowers, to assess whether perceived or behavioral aspects of cognition change over the course of a season, and to identify psychological and cognitive responses in student-athletes that are related at peak training. The effects of four weeks of intensified training influences resting metabolic rate and exercise regulation in elite rowers.

04
2) Multicomponent Training Distress Scale (MTDS) The MTDS was administered one week prior (PRE), each week during, and one-week after completion of the training cycle (POST) to assess training-related mood disturbance. Questionnaires were consistently dispensed after breakfast and before the second morning training session on the Friday of each respective training week. Responses to the 22-item questionnaire were anchored on a Likert scale from 0 being "Not at all" to 5 being "Extremely". To describe the sleep and training load (TL) patterns, to study the relationship between sleep and TL in a cohort of elite female gymnasts of different age groups during a 14-week training period. The effect of composed adaptogenic formula formed from l-arginine, whey protein concentrate, ginseng and cocoa powder on the physical and metabolic changes that occur to athletes during performance of intensive exercises where energy supply depends mainly on anaerobic oxidation.  showering. Actigraphy data were recorded in 1-min period lengths and evaluated using Actiware software (Phillips Respironics, Andover, MA). The athletes reported the following data in their sleep diary: bedtime, wake time and naps during the day. n/a 6) Epworth Sleepiness Scale (ESS) and 4) Pittsburgh Sleep Quality Index (PSQI). The ESS Score ranges from 0 to 24 points. A score between 0-9 points is matched as no daytime sleepiness (DS) or normal DS and a total score above 9 is considered abnormal DS. The PSQI score ranges from 0-21 points. A total score equal to or less than 5 points is associated with good sleep quality (SQ) and the total score above 5 is considered poor SQ. Validity and reliability references were provided. To investigate the sportspecific performance effect of a brief afternoon nap on high-level Asian adolescent student-athletes that were habitually short sleepers. n/a 24) Actigraph (GT3X activity monitors, FL, USA) and 3) Wireless dry electroencephalographic (EEG) sensor (Zeo, MA, USA). On the night prior to each experimental session, participants wore the GT3X activity monitors, the data were scored and analyzed using ActiLife 6.9.2 and using the Sadeh algorithm which has been validated in an adolescent population and shown to have an overall high accuracy to that of polysomnography.
The actigraph collected the following sleep variables: (1) bedtime, (2) wake time, (3)  Participants were asked to record their bedtime and pre-sleep fatigue prior to a night-time sleep period and their get-up time, and sleep quality as soon as practicable after waking. The participants were instructed not to remove their activity monitor except when showering, swimming, or submersion. Data derived from the sleep diaries and wrist activity monitors were used to determine participants' amount and quality of sleep. All time was the sleep diary indicated that the participant was lying down attempting to sleep and (2) The activity counts derived from the activity monitor were sufficiently low to indicate that the participant was immobile. Once these conditions were met simultaneously, time was scored as sleep. This scoring process was conducted using Phillips Respironics'Actiwatch algorithm with sensitivity at 'medium'. The following sleep variables were derived from the activity monitor and sleep diary. Subjective sleep quality the participants' self-rating of sleep quality on a five-point Likert scale. Validity and sensitivity information were reported.  Age: 19 ± 1 y Regional The effects of two types of partial sleep deprivation at the beginning and the end of the night on mood, cognitive performances, biomarkers of muscle damage, haematological status and antioxidant responses before and after repeated-sprint exercise in the post-lunch dip.
n/a 5) Pittsburgh Sleep Quality Index (PSQI), 7) Epworth Sleepiness Scale, 15) Sleep diary, and 22) A Likert-type scale ranging from 1 to 7 (sleep quality). Selfadministered questionnaire to measure the level of daytime sleepiness. If the subjective sleepiness score exceeds 6 then the participant is considered as sleepy. The Hooper Index is a psychological self-reporting scale of sleep quality using a 7 points subjective rating scales ranging from 1 "very, very low" to 7 "very, very high". Validity and reliability information were provided. The sleep-wake threshold that has a high sensitivity to sleep (≥80 activity counts is scored as wake), generating the smallest mean biases compared with PSG for total sleep time (TST), sleep efficiency (SE) and wake after sleep onset (WASO) among endurance athletes (Sargent et al., 2016). The sleep variables were as follows: time in bed (TIB) was defined as the time between lights off (bedtime) and sleep end; sleep onset latency (SOL) was defined as the time between lights off and sleep onset; TST was defined as the time spent asleep, as determined from sleep start to sleep end, minus any wake time; SE was defined as the TST divided by the TIB (expressed as a percentage); WASO was defined as the total wake time, according to the epochby-epoch wake/sleep categorization; and the fragmentation index (FI) was defined as the sum of the moth. 3) Spiegel Sleep Inventory (SSI) to perceived sleep quality (Léger et al., 2006). The SSI is a self-administered questionnaire composed of six questions (score: 1-5) regarding sleep start, sleep quality and length, nocturnal awakenings, dreams and feeling refreshed in the morning.

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Likert-type scale ranging from 1 to 5 rating scale (sleep quality) This question was "How would you evaluate the quality of your sleep in the past few days?" Participants reported their sleep quality on a Likert-type scale as follows: 1 = very bad, 2 = bad, 3 = regular, 4 = good and 5 = excellent.

Swimmers n=130 Adolescent
Investigate sleep duration and intraindividual night-to-night variability of sleep duration as well as wakening after sleep onset (WASO) and sleep efficiency in young Icelandic swimmers.
To estimate the sleep duration of participants, TST was obtained, in addition to estimation of the total time spent in bed, total rest time. The SD of TST for each individual was used to describe within subject night-to-night variability (in minutes). WASO was used for estimation of sleep quality. WASO refers to periods (in minutes) of wakefulness occurring after sleep onset. Sleep efficiency was calculated as minutes of total sleep divided by the total time in bed and multiplied by 100 32 .

Mah
Cyclists (n=11, M) Age = 28.8 ± 4.5 y Ellite Effects of consecutive days of sleep restriction on physical performance and dynamic movement via maximal vertical jump, joint coordination and psychomotor response time in elite athletes.
1 Actigraphy (AW-64, Philips Respironics, Andover, MA) to monitor sleep/wake activity on the wrist of the non-dominant hand 24-h per day with the exception of bathing and training. Recorded daily sleep journals that included sleep/wake activity such as reported time in bed, time asleep, minutes awake and wake time. n/a Activity monitor (Actical MiniMitter/ Philips Respironics, Bend, OR). Participants recorded bed-, and wake-times in a diary in order to crosscheck sleep/wake states identified with actigraphy. The total sleep obtained (i.e., total sleep time -TST), and the percentage of time in bed spent asleep (i.e., sleep efficiency -SE) were calculated for all sleep periods. Likert Scale -sleep quality (SQ) according to a 5-point Likert scale (i.e., 1 = very good, 2 = good, 3 = average, 4 = poor and 5 = very poor).